【摘要】：在網(wǎng)絡(luò)信息資源劇增的今天,如何從海量且雜亂無章的Web數(shù)據(jù)中查找有價(jià)值的信息已經(jīng)成為一個(gè)重要難題。語義網(wǎng)通過對(duì)當(dāng)前的萬維網(wǎng)進(jìn)行擴(kuò)展允許基于語義web信息的表示和處理,為Web信息提供形式化的含義,使跨應(yīng)用、團(tuán)體和企業(yè)的數(shù)據(jù)共享與重用成為了可能。 RDF作為語義網(wǎng)廣泛的數(shù)據(jù)結(jié)構(gòu),實(shí)現(xiàn)了Web上信息資源的語義描述,是語義Web的基礎(chǔ),人們對(duì)它的研究已經(jīng)成為了熱點(diǎn)之一。隨著RDF的應(yīng)用范圍的不斷擴(kuò)大,傳統(tǒng)的數(shù)據(jù)庫管理系統(tǒng)目前已經(jīng)不能滿足人們?nèi)找嬖鲩L(zhǎng)的需求,因此對(duì)RDF元數(shù)據(jù)查詢和存儲(chǔ)的研究越來越重要,本文就是在這種背景之下對(duì)RDF元數(shù)據(jù)的查詢和存儲(chǔ)進(jìn)行了一些相關(guān)的研究。 主要完成的工作主要有： 首先本文對(duì)RDF元數(shù)據(jù)查詢和存儲(chǔ)的現(xiàn)狀、概念背景進(jìn)行了介紹,包括語義網(wǎng)的相關(guān)概念標(biāo)準(zhǔn)、語義網(wǎng)的七層體系結(jié)構(gòu)、元數(shù)據(jù)、XML、RDF、本體技術(shù)等等,為下文RDF的查詢和存儲(chǔ)的研究奠定了基礎(chǔ)。 其次對(duì)現(xiàn)有的存儲(chǔ)和查詢技術(shù)進(jìn)行了簡(jiǎn)要概括,分析了當(dāng)前經(jīng)典的RDF數(shù)據(jù)查詢和存儲(chǔ)的技術(shù),并重點(diǎn)對(duì)W3C推薦的查詢語言SPARQL進(jìn)行了分析。 接著分析了查詢效率低下原因是現(xiàn)存的存儲(chǔ)技術(shù)大多存在自身連接的問題,于是本文參考垂直分塊思想,在現(xiàn)有的三級(jí)索引技術(shù)之上,增加索引結(jié)構(gòu)來解決三級(jí)索引結(jié)構(gòu)的局限性問題。改進(jìn)后的索引結(jié)構(gòu)使得在查詢語句可以不同情況下進(jìn)行不同處理,進(jìn)而提高查詢效率。本文還在查詢時(shí)使用了能夠選擇最優(yōu)的計(jì)算順序的動(dòng)態(tài)規(guī)劃算法對(duì)查詢進(jìn)行優(yōu)化,使得查詢時(shí)可以選擇更好的連接順序,進(jìn)一步提高了查詢效率。 最后在改進(jìn)的存儲(chǔ)方案和查詢優(yōu)化基礎(chǔ)上搭建了原型系統(tǒng),并通過原型系統(tǒng)對(duì)提出的改進(jìn)存儲(chǔ)方案和查詢優(yōu)化進(jìn)行實(shí)驗(yàn)驗(yàn)證,實(shí)驗(yàn)結(jié)果表明本文提出的方法確實(shí)能夠明顯的提高查詢的效率。
[Abstract]:Nowadays, with the rapid increase of network information resources, how to find valuable information from massive and unorganized Web data has become an important problem. By extending the current Web to allow the representation and processing of semantic web information, the semantic Web provides a formal meaning for Web information, making it possible to share and reuse data across applications, groups and enterprises. As an extensive data structure of semantic web, RDF has realized the semantic description of information resources on Web, which is the basis of semantic Web. With the continuous expansion of the scope of RDF application, the traditional database management system can no longer meet the increasing needs of people, so the research of RDF metadata query and storage is becoming more and more important. In this paper, we do some research on RDF metadata query and storage under this background. The main work is as follows: firstly, this paper introduces the current situation of RDF metadata query and storage, and the concept background, including the semantic Web related concept standards, semantic Web seven-tier architecture, metadata, XML,RDF,. Ontology technology and so on, for the following RDF query and storage research laid the foundation. Secondly, the existing storage and query technologies are briefly summarized, the current classic RDF data query and storage techniques are analyzed, and the W3C recommended query language SPARQL is emphatically analyzed. Then, the paper analyzes the reason for the inefficiency of query is that most of the existing storage technologies have the problem of joining themselves, so this paper refers to the idea of vertical partitioning, and based on the existing three-level index technology, Add index structure to solve the limitation problem of tertiary index structure. The improved index structure enables the query statements to be processed differently under different circumstances, thus improving the query efficiency. This paper also uses the dynamic programming algorithm which can select the optimal computing order to optimize the query, so that the query can choose a better join order, and further improve the query efficiency. Finally, a prototype system is built on the basis of the improved storage scheme and query optimization, and the proposed improved storage scheme and query optimization are verified by the prototype system. Experimental results show that the proposed method can obviously improve the efficiency of the query.
【學(xué)位授予單位】：廣西師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP391.1;TP333

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本文編號(hào)：2363513